This disclosure relates to a method and apparatus for calibrating intelligent antennas in a telecommunications network. More particularly, this disclosure relates to a method and apparatus for optimally combining noisy calibration measurements in order to obtain a composite statistically useful result.
While the disclosure is particularly directed towards intelligent antenna calibration, and will be thus described with specific reference thereto, it will be appreciated that the disclosure may have usefulness in other fields and applications. For example, this disclosure may be used for a variety of calibration techniques and/or methods.
By way of background, intelligent antennas are antennas that are used in radio communication systems that may alter the phase of a signal in order to steer it in an optimal direction. In order to steer the signal in the proper direction, it is important to know the differences in the few attributes of the pairs of antenna. One way of doing this is to calibrate the separate antennas in order that we know the phase difference, the gain difference, and delay difference in each of the pairs of antenna.
In many systems, a low level calibration signal is sent to each of the antennas in order to define these attributes. The calibration signal is often sent at a very low level in order to not interfere with the communication signals. Once the calibration signal is returned, a measurement is taken in order to determine the calibration offsets.
Because these antennas are physically in different locations, an identical signal sent to each antenna will have inherent differences. This is mostly due to the cables connecting them. The calibration signal is sent out in order to determine these differences and offer corrections for them. However, because these calibration signals are sent at a very low power, it is often the case that noise will interfere with the calibration signal. When noise interferes with this calibration signal the reading is often inaccurate and not reliable. Unfortunately, in order to properly calibrate these intelligent antenna a certain level of accuracy is required. When the Signal to Noise Ratio (SNR) is too low, the reading must be disregarded and another one must be taken.
Significant time and energy is spent sending and receiving low level calibration signals that cannot be used due to noise. Therefore, there is a need in the industry to find a use for low level calibration signals with a relatively low SNR. Furthermore, there is a need in the industry for a system and method that makes calibration techniques more efficient.
The present disclosure contemplates a new and improved system and method that resolves the above-referenced difficulties and others.